Here's the results from diehard for yours (seed 123412341234 - assuming order of operations was the same)

While the rate of outlier p values (p < 0.01 or p> 0.99) was high for the number of samples (also there were two p=1.000000 values [See DNA tests for bits 32-30]), its probably sufficient levels of randomness for transcendence as well as being far faster than mine. (I tested; yours is ~3-4 orders of magnitude faster than mine)

also heres the mk3b algorithm I used (super slow though) - the different versions were just slight refinements that lowered the number of (0.5-|p-0.5|) < 1% - it also seems that 123412341234 is a particularly rough seed:

Ok, so for fun (since I already know the standard c rand() function is awful I didnt bother to test it) I decided to try out the simple .net rng...

Turns out that pixels knocks it flat (with around the same runtime!) - even with its own two 1.0's, the standard .net one is... just look at it! The number of 1.000000's is... This is without a doubt a complete fail.

Nice to see those results. I'm a bit surprised by the failure of the .net rng. I would think that by now a standard rng would provide better quality output.
I'm most happy to see that my seededRandom is not that bad, although it seems that it is not particularly good either

It seems you put a lot more work in your, I'll take a better look at it later today.

For its speed, its great - Generally failing one test with a simple fast algorithm isnt bad - I was working on getting mine to produce a distribution of p-values that were appropriate (ie, a combination that should only happen 10% of the time should only happen ~10% of the time, etc), but at the cost of it plodding along slowly.